I am a Data Engineer specialized in web scraping, data pipeline development, and workflow automation. I design and implement scalable data solutions that transform raw, unstructured data into structured, actionable insights.

My expertise includes building robust web scraping systems using Python (Requests, BeautifulSoup, Selenium), handling dynamic content, anti-bot considerations, and large-scale data extraction. I focus on reliability, maintainability, and clean output formats (CSV, JSON, Excel, database ingestion).

In data engineering workflows, I develop ETL/ELT pipelines to extract, clean, transform, and load data into SQL and NoSQL databases. I work with relational databases (PostgreSQL, MySQL) as well as NoSQL systems (MongoDB), ensuring optimized schema design and efficient querying.

I also build automated Python scripts for recurring tasks, data synchronization, API integrations, and business process automation. I design REST APIs for data exposure and integration between systems, and I define KPIs to monitor performance and business metrics.

My technical stack includes:
Python (automation, scraping, data processing)
SQL & NoSQL databases
ETL / ELT pipeline design
REST API development
Docker for containerization
ELK Stack (Elasticsearch, Logstash, Kibana) for monitoring and logging
Prefect for workflow orchestration
Data validation and cleaning pipelines

I prioritize:
Clean, maintainable code
Scalable architectures
Clear documentation
Reliable delivery and communication

I am available for:
Web scraping & data extraction projects
Data pipeline design and optimization
Database design and query optimization
Automation systems
API development
Monitoring and KPI implementation